Image reading apparatus reading an original while transporting the same

ABSTRACT

An image reading apparatus includes, with the purpose of accurately correcting noise in an image due to dust on a platen, three line sensors spaced from each other in a sub scanning direction to scan an original in the sub scanning direction, a platen between the original and the three line sensors, a moving mechanism for moving the platen, a noise detection processor detecting a noise pixel from each of multiple data output from the three line sensors, a second pixel extractor extracting a second pixel present in first data for correcting the noise pixel, based on a value of a first pixel present in second data different from the first data and corresponding to the same location on the original as the noise pixel, and a corrector correcting the noise pixel based on the extracted second pixel.

This application is based on Japanese Patent Application No. 2004-286212filed with the Japan Patent Office on Sep. 30, 2004, the entire contentof which is hereby incorporated by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to image reading apparatuses andparticularly to image reading apparatuses reading an original whiletransporting it.

2. Description of the Related Art

Conventionally digital copiers and similar image reading apparatusesemploy a technique referred to as so-called “reading an original whilepassing the original.” More specifically, an original is transportedrelative to a fixed line sensor in a sub scanning direction orthogonalto the line sensor as the original is read.

Such image reading apparatus is provided with a transparent platenbetween the original and the line sensor to fix a position at which atransported original is read. The original reflects light which is inturn received via the platen by the line sensor.

As such, if dust, paper particles, flaws or other similar foreignmatters (hereinafter generally referred to as “dust”) adhere on theplaten's reading position, the line sensor will read the dust whilereading a transported original. This provides an output image with noisein the form of a line in the sub scanning direction.

Japanese Laid-Open Patent Publication No. 2002-77584 discloses atechnique for improving the image quality by replacing image data of aregion where noise in the form of a line appears in the sub scanningdirection with image data of regions adjacent to and located onrespective sides of the region having the line noise.

However, the image data of the adjacent regions on respective sides ofthe noise region is not always similar to the image data of the noiseregion. For example, in the adjacent regions, an edge region could bepresent or the color could suddenly change. More specifically, it issupposed here that an original has two regions that are one region ofred and the other region of black and a noise region is present in thered region near the boundary between the two regions. In this case,although the noise region should be corrected to red, the noise regioncould be corrected to black due to the presence of the adjacent blackregion.

SUMMARY OF THE INVENTION

The present invention has been made to overcome the above disadvantageand contemplates an image reading apparatus capable of accuratelycorrecting noise generated in an image by dust existing on a platen.

To achieve the above object the present invention in one aspect providesan image reading apparatus including: a plurality of line sensorsarranged to be mutually spaced in a sub scanning direction to scan anoriginal in the sub scanning direction; a platen arranged between theoriginal and the line sensors; a mover moving the platen at a raterelative to the line sensors, the rate being different from that of theoriginal relative to the line sensors; an extractor extracting a featurepixel having a predetermined feature from each of a plurality of dataoutput from the line sensors; a detector comparing pixels of theplurality of data corresponding to a single location on the original todetect the feature pixel extracted from first data of the plurality ofdata, as a noise pixel if the feature pixel is not a feature pixel forthe plurality of data other than the first data; a second pixelextractor extracting, based on a value of a first pixel present insecond data different from the first data and corresponding to the samelocation on the original as the noise pixel, a second pixel present inthe first data for correcting the noise pixel; and a correctorcorrecting the noise pixel based on the extracted second pixel.

In accordance with the present invention the original is scanned in thesub scanning direction by a plurality of line sensors spaced in the subscanning direction and between the original and the line sensors thereis provided the platen moving at a rate relative to the line sensors,the rate being different from that of the original relative to the linesensors. When the platen has dust adhering thereon, the dust is read bythe line sensors sequentially. As the platen is moved at a rate relativeto the line sensors, the rate being different from that of the originalrelative to the line sensors, the dust on the platen is read by eachline sensor at a different location of the original. The image readingapparatus detects a noise pixel from each of a plurality of data outputfrom the line sensors, compares pixels of the plurality of datacorresponding to a single location on the original to detect the featurepixel extracted from first data among the plurality of data, as a noisepixel if the feature pixel is not a feature pixel for the plurality ofdata other than the first data, and determines a second pixel used forcorrecting the noise pixel based on a first pixel present in second datadifferent from the first data in which the noise pixel is present. Thenoise generated by reading dust is corrected using a pixel selected fromneighboring pixels. The image reading apparatus capable of improvingimage quality after correction can thus be provided.

The foregoing and other objects, features, aspects and advantages of thepresent invention will become more apparent from the following detaileddescription of the present invention when taken in conjunction with theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a perspective view of an MFP including an image readingapparatus in one embodiment of the present invention.

FIG. 2 schematically shows the image reading apparatus's internalstructure.

FIG. 3 is a perspective view of a mechanism employed to oscillate aplaten.

FIGS. 4A-4C are diagrams for illustrating a theory of detecting noisegenerated by reading dust from a read image.

FIG. 5 is a rear plan view of the platen.

FIG. 6 shows a position on a platen read by a reader.

FIG. 7 is a block diagram showing a configuration of an image processorof the image reading apparatus in the present embodiment.

FIGS. 8A and 8B represent one example of RGB signal output from thereader.

FIG. 9 is a block diagram showing a configuration of a noise detectionprocessor of the image reading apparatus in the present embodiment.

FIGS. 10A-10F show an edge extraction filter by way of example.

FIG. 11 is a flowchart showing a flow of a process followed by adeterminer of the noise detection processor.

FIG. 12 is a flowchart showing a flow of a noise pixel correctionprocess in step S04 of FIG. 11.

FIG. 13 is a flowchart showing a flow of a correction process followedby a noise corrector.

FIG. 14 is a flowchart showing a flow of an R-signal correction processin step S53 of FIG. 13.

FIGS. 15A and 15B show exemplary search ranges.

FIG. 16 is a flowchart showing a flow of a determination process for acandidate pixel in step S103 of FIG. 14.

FIG. 17 is a flowchart showing a flow of a G-signal correction processin step S55 of FIG. 13.

FIG. 18 is a flowchart showing a flow of a determination process for acandidate pixel in step S103 of FIG. 17.

FIG. 19 is a flowchart showing a flow of a B-signal correction processin step S57 of FIG. 13.

FIG. 20 is a flowchart showing a flow of a determination process for acandidate pixel in step S103 of FIG. 19.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

Hereinafter reference will be made to the drawings to describeembodiments of the present invention. In the following description, likecomponents are denoted by like reference characters and also identicalin name and function.

FIG. 1 is a perspective view of a multi-function peripheral (MFP)including an image reading apparatus in one embodiment of the presentinvention. With reference to the figure, the MFP includes an imagereading apparatus 10 operative to read an original image, and an imageforming apparatus 20 provided under image reading apparatus 10. The MFPforms an image read by image reading apparatus 10 on a sheet of paper orsimilar recording medium. Furthermore, the MFP includes a communicationsinterface to connect with a facsimile device, a local area network(LAN), a public line or similar network.

FIG. 2 schematically shows an internal configuration of image readingapparatus 10. Image reading apparatus 10 includes an automatic documentfeeder (ADF) 101 and a main body 103. ADF 101 includes an upperrestraint plate 203 guiding a transported original in the vicinity of anoriginal reading position, a timing roller pair 201 transporting theoriginal to the original reading position, and a roller pair 202transporting the original having moved past the reading position.

Main body 103 includes a platen 205 formed of a transparent member, asheet passage guide 207 forming a portion of a path of the original, asource of light 206 illuminating the original at the reading position, areflector member 208 reflecting the light emitted from the source oflight, a reader 213 having three line sensors arranged in a sub scanningdirection, a reflector mirror 209 arranged to reflect light reflectedfrom the original and guide the reflection of light to reader 213, alens 211 focusing the reflection of light on reader 213, an imageprocessor 215 processing an electrical signal output from reader 213, amotor 219 operative to oscillate platen 205, and a motor controller 217operative in response to a control signal received from image processor215 to control the driving of motor 219.

An original 200 is transported by timing roller pair 201 between platen205 and upper restraint plate 203 in a direction D1. The original beingtransported has its image read at a reading position L by reader 213successively. ADF 101 transports an original in the sub scanningdirection, as seen at a reading position L. During the image readingoperation, platen 205 is oscillated by motor 219 in a direction D2.Platen 205 oscillates in a direction substantially parallel to the subscanning direction.

Reader 213 includes three line sensors each having a plurality ofphotoelectric conversion elements arranged in a main scanning directionsubstantially perpendicular to the sub scanning direction. The threeline sensors have filters, respectively, different in spectralsensitivity and receive light reflected from an original through thefilters. More specifically, the sensors have filters transmitting lightof waveforms of red (R), green (G) and blue (B). Thus, the line sensorhaving the filter of red (R) outputs an R signal, an electrical signalindicating an intensity of red light of light reflected from anoriginal, the line sensor having the filter of green (G) outputs a Gsignal, an electrical signal indicating an intensity of green light oflight reflected from the original, and the line sensor having the filterof blue (B) outputs a B signal, an electrical signal indicating anintensity of blue light of light reflected from the original.

The three line sensors are arranged in the sub scanning direction in apredetermined order with a predetermined distance therebetween. In thisexample, the line sensors are spaced by a distance corresponding tothree original reading lines, and arranged, red first, followed by greenand then blue as seen in the direction in which an original istransported, although the line sensors may be spaced by differentdistances and arranged in different orders.

The three line sensors thus spaced and arranged simultaneously receiveat the same timing the light reflected by an original at differentlocations. As such, the light reflected by the original at a location isinitially received by the red light receiving line sensor, subsequentlyby the green light receiving line sensor, and finally by the blue lightreceiving line sensor. This delay is adjusted by image processor 215, aswill be described later.

Note that while in the present embodiment reader 213 is provided withthree line sensors, it may be provided with four or more line sensors.

FIG. 3 is a perspective view showing a mechanism employed to oscillatethe platen. With reference to the figure, platen 205 is held by a platenholder 221 held slidably in the sub scanning direction by a guide 220fixed to the main body of image reading apparatus lo. Platen holder 221has one surface with two arms 222 connected thereto. Arm 222 has theother end provided with a circular hole.

A shaft 224 at portions corresponding to the two arms 222 has two cams223 attached thereto. Furthermore, shaft 224 has one end with a gear 225attached thereto. Gear 225 is arranged to mesh with a gear 226 linked bya belt to the motor 219 drive shaft. As motor 219 runs, the motor'srotation is transmitted by the belt to gear 226, and gear 226 thusrotates. As gear 226 rotates, gear 225 and shaft 224 rotate.

Cam 223 is arranged in the circular hole of arm 222. As such, as shaft224 rotates, the two cams 223 accordingly provide rotation, which isconverted to translation movement of platen holder 221.

Note that platen 205 may be oscillated by a mechanism other than thatdescribed above. For example, the platen may be oscillated by amechanism employing a driving source, such as a piston utilizing anelectromagnet, air pressure, hydraulic pressure and the like, causinglinear movement.

Platen 205 is oscillated parallel to the sub scanning direction. Whenplaten 205 is moving in a direction opposite that in which an originalis transported, platen 205 and the original move in the oppositedirections. As such, the speed of platen 205 relative to line sensors213R, 213G, 213B and that of the original relative to the line sensorsare different. In contrast, when platen 205 is moving in the directionin which the original is transported, the speed of platen 205 and thatof the original transported are the same in direction. Preferably, theyshould be different in rate. Note that while herein platen 205 isoscillated parallel to the sub scanning direction, the platen may beoscillated in different directions.

In the present embodiment image reading apparatus 10 detects noisegenerated by dust adhering on platen 205 from a read image in accordancewith a theory as described hereinafter. FIGS. 4A-4C are diagrams forillustrating the theory. For the sake of illustration, an original andplaten 205 are transported in the figures in a direction indicated by anarrow, and platen 205 moves at a rate which is the same in direction asand twice in magnitude that at which the original is transported.Furthermore for the sake of illustration the three line sensors are redlight, green light and blue light receiving line sensors arranged redfirst, followed by green and then blue in the direction in which theoriginal is transported, with a distance corresponding to three linestherebetween R, G and B indicate outputs of the red light, green lightand blue light receiving line sensors, respectively.

FIG. 4A is a diagram for illustrating interline correction. The image ofa portion of the original is initially read by the red light receivingline sensor arranged most upstream in the direction in which theoriginal is transported. The image is then transported by a distancecorresponding to four lines, and read by the green light receiving linesensor. The image is further transported by a distance corresponding tofour lines, and read by the blue light receiving sensor.

Thus an image located in an original at a single location is read bythree line sensors at different times. As such, the three line sensorsoutput signals offset in timing. Interline correction synchronizes thesignals output from the three line sensors so that the signals allcorrespond to a single location in the original. More specifically,output R is delayed by eight lines and output G is delayed by fourlines.

Interline corrected outputs R, G and B are composited to provide acomposite output, which corresponds to outputs R, G and B read at asingle location in an original and composited together.

FIG. 4B is a diagram for illustrating a composite output provided whendust adhering on a platen is read. The dust adhering on platen 205 isinitially read by the red light receiving line sensor arranged mostupstream in the direction in which an original is transported. The dustis transported by a distance corresponding to four lines, and read bythe green light receiving line sensor. Since platen 205 moves in thesame direction as the original at a rate twice that at which theoriginal is transported, the dust moves by four lines in a period oftime required for a line sensor to read the original by two lines. Assuch, between the time point at which the red line sensor reads the dustand that at which the green line sensor reads the dust there isintroduced an offset by a period of time corresponding to reading twolines. Furthermore, the dust is transported by a distance correspondingto four lines, and read by the blue light receiving line sensor. Sinceplaten 205 moves in the same direction as the original at a rate twicethat at which the original is transported, between the time point atwhich the green line sensor reads the dust and that at which the blueline sensor reads the dust there is introduced an offset by a period oftime corresponding to reading two lines.

By interline correction the red light receiving line sensor reading thedust outputs R delayed by eight lines and the green light receiving linesensor reading the dust outputs G delayed by four lines. As such,interline corrected outputs R, G and B composited together provide acomposite output in which outputs R, G and B with the dust read are notcomposited at the same timing, offset by two lines.

Note that the figure shows a composite output provided when paperparticles or similar white dust adhere on platen 205 and a blackoriginal is read. Despite that the white dust is read, the compositeoutput is not white but rather an output of blue, green and red dividedin three lines.

FIG. 4C is another diagram for illustrating a composite output providedwhen dust adhering on a platen is read. The figure shows an example ofreading dust having a size corresponding to ten lines in the subscanning direction. Platen 205 moves in the same direction as anoriginal at a rate twice that at which the original is transported. Assuch, the dust is read as having a size corresponding to five lines;

The dust adhering on platen 205 is initially read by the red lightreceiving line sensor arranged most upstream in the direction in whichthe original is transported. The dust is then transported by a distancecorresponding to four lines, and read by the green light receiving linesensor. Between the time point at which the red line sensor reads thedust and that at which the green line sensor reads the dust there isintroduced an offset by a period of time corresponding to reading twolines. The dust further is transported by a distance corresponding tofour lines, and read by the blue light receiving line sensor. Betweenthe time point at which the green line sensor reads the dust and that atwhich the blue line sensor reads the dust there is introduced an offsetby a period of time corresponding to reading two lines.

By interline correction the red light receiving line sensor reading thedust outputs R delayed by eight lines and the green light receiving linesensor reading the dust outputs G delayed by four lines. As such,interline corrected outputs R, G and B composited together provide acomposite output in which outputs R, G and B by five lines with the dustread are not composited at the same timing, offset by two lines. Notethat the figure shows a composite output provided when paper particlesor similar white dust adhere on platen 205 and a black original is read.Despite that the white dust is read, the composite output is an outputvarying in color, first in blue, followed by cyan, white yellow and thenred.

The dust adhering on platen 205 is thus divided in an image into aplurality of lines, which are extracted for each color as a featurepoint to detect noise. Furthermore, such division also reduces noisecaused by reading the dust.

FIG. 5 is a plan, rear view of the platen. With reference to the figure,platen 205 has one end with a mark 205A having a single color and ageometry having in the main scanning direction a length varyingdepending on the position in the sub scanning direction. In thisdescription, mark 205A is a black triangle. Furthermore, mark 205A hasone side arranged parallel to one side of platen 205.

Reader 213 or a sensor provided separate from reader 213 and fixed tomain body 103 can be used to detect the length of mark 205A in the mainscanning direction to detect the position of platen 205 relative toreader 213.

FIG. 6 shows a location on platen 205 read by reader 213. Reader 213 hasline sensors 213R, 213G and 213B having filters of red (R), green (G)and blue (B), respectively, arranged in a direction in which an originalis transported D1, red first, followed by green and then blue.

Line sensors 213R, 213G and 213B receive light transmitted throughplaten 205 at regions 205R, 205G and 205B, respectively. Regions 205R,205G and 205B are arranged to be spaced by three lines. The originalinitially moves past region 205R, then region 205G and finally region205B. As such, light reflected by the original at a location isinitially received by the red light receiving line sensor 213R, then thegreen light receiving line sensor 213G, and finally the blue lightreceiving line sensor 213B. Line sensors 213R, 213G, 213B spaced bythree lines thus will not simultaneously receive light reflected by theoriginal at a single location.

If platen 205 has adhering thereto dust 300 having a maximal length ofat most four lines, then dust 300 will not exist at two or more ofregions 205R, 205G, 205B concurrently as platen 205 moves oscillatingparallel to the sub scanning direction. FIG. 6 shows a case where dust300 exists at region 205G. In this case, light reflected by dust 300 isreceived only by line sensor 213G and not received by line sensor 213Ror 213B.

Furthermore, as platen 205 oscillates, dust 300 will exists at differentregions. More specifically, when platen 205 moves in direction D1, dust300 initially exists at region 205R, then region 205G and finally region205B. In contrast, when platen 205 moves in a direction oppositedirection D1, dust 300 exists initially at region 205B, then region205G, and finally region 205R.

As such, light reflected by dust 300 is received in such an order thatwhen platen 205 moves in direction D1 the light is received initially byline sensor 213R, then line sensor 213G and finally line sensor 213B andwhen platen 205 moves opposite to direction D1 the light is receivedinitially by line sensor 213B, then line sensor 213G, and finally linesensor 213R.

When platen 205 is moving in the direction in which the original istransported, noise resulting from reading of the dust appears first inthe R signal output from line sensor 213R, then in the G signal outputfrom line sensor 213G and finally in the B signal output from linesensor 213B. When platen 205 is moving in the direction opposite to thedirection in which the original is transported, noise resultant fromreading of the dust appears first in the B signal output from linesensor 213B, then in the G signal output from line sensor 213G andfinally in the R signal output from line sensor 213R. In other words, inwhat order the noise appears in the signals is determined by thedirection in which platen 205 is moved. The order of the signals havingnoise therein detected can be determined to improve precision indetecting the noise.

FIG. 7 is a block diagram showing a configuration of the image processorof the image reading apparatus in the present embodiment. With referenceto the figure, image processor 215 receives R, G and B signals fromreader 213. Image processor 215 includes an analog/digital (A/D)converter 251 receiving an analog signal from reader 213 to convert theanalog signal to a digital signal, a shading corrector 253 correctinguneven illumination provided by the source of light 206 or the like, aninterline corrector 255 synchronizing the R, G and B signals to be asingle line of an original, a color aberration corrector 257 correctingdistortion in the main scanning direction introduced by lens 211, anoise detection processor 259 detecting noise from each of the R, G andB signals, a noise corrector 260 effecting a process to correct a noisepixel, a controller 263 generally controlling image processor 215, and aprinter interface 261 used to output an image to image forming apparatus20. Controller 263 has a position detector 265 connected thereto todetect the position of platen 205. Position detector 265 detects alength of mark 205A of platen 205 in the main scanning direction.

Interline corrector 255 delays the R and G signals by eight and fourlines, respectively, to synchronize the R, G and B signals to be asingle line of the original, since as has been described previously,line sensors 213R, 213G, 213B are spaced in the sub scanning directionby a distance corresponding to three lines.

Noise detection processor 259 receives the R. G and B signals from coloraberration corrector 257 and from controller 263 the position of platen205 and a direction in which platen 205 moves. Noise detection processor259 detects a noise pixel for each of the R, G and B signals receivedfrom color aberration corrector 257, and outputs to noise corrector 260and controller 263 logical signals of “1” and “0” indicating a noisepixel and a pixel other than a noise pixel, respectively. The detailwill be described later.

Noise corrector 260 receives the R, G and B signals from coloraberration corrector 257 and from noise detection processor 259 receivesfor each of the R, G and B signals logical signal of “1” and “0”indicating a noise pixel and a pixel other than a noise pixel,respectively.

Noise corrector 260 replaces, for each of the R,. G and B signals, basedon a logical signal corresponding thereto, the value of a pixeldetermined as a noise pixel with that of a neighboring non-noise pixel.Noise corrector 260 outputs to the printer interface the R, G and Bsignals with the noise pixel replaced with the neighboring pixel.

Controller 263 receives the position of platen 205 from positiondetector 265 and from noise detection processor 259 logical signals of“1” and “0” indicating a noise pixel and a pixel other than noise pixel,respectively. Controller 263 determines from these signals the dust'slocation on platen 205. More specifically, it determines the position ofplaten 205 in the sub scanning direction from the position of platen 205and a logical signal's line number, and the position of platen 205 inthe main scanning direction from a location of a noise pixel of thelogical signal.

The noise detection process will more specifically be describedhereinafter. As has been described with reference to FIG. 6, linesensors 213R, 213G and 213B will read different locations on an originalat the same timing. Interline corrector 255 synchronizes the R, G and Bsignals' lines to obtain R, G and B signals having read a singlelocation on the original.

As such, if platen 205 has dust adhering thereon, R, G and B signalshaving read a single location on an original have one of them affected.

FIGS. 8A and 8B represent an example of RGB signal output from thereader. FIG. 8A shows an example of reading a white area of an originalwith black dust adhering on the platen's region 205R corresponding toline sensor 213R. Line sensor 213R reads a portion of the original withthe black dust on region 205R. Subsequently, the portion of the originalmoves to regions 205G, 205B corresponding to line sensors 213G, 213B,when the dust does not exist on regions 205G, 205B, since the originaland platen 205 moves at different rates. As such line sensors 213G, 213Bwill read the original's white area. Consequently, only an R signaloutput from line sensor 213R is reduced in lightness and line sensors213G, 213B output G and B signals high in lightness. Note that herein,“lightness” indicates a value output from the three line sensors 213R,213G, 213B corresponding to a reflection of light.

The FIG. 8A RGB signals' combination is seldom output when an originalis read without dust adhering thereto. A combination closest thereto isa case where an area of cyan, a color complementary to red, is read.FIG. 8B represents RGB signal output from reader 213 when an original'scyan area is read. The R signal significantly drops in lightness, andthe G and B signals also drops in lightness. As such, the variation inlightness of the R signal significantly dropping in lightness can bedetected by using a threshold value Red1(R).

The FIG. 8A RGB signal and the FIG. 8B RGB signal are significantlydifferent in whether the B and G signals are affected. By detecting thisdifference, black dust can be detected as noise without detecting a cyanline erroneously as noise. As such, the B signal's variation inlightness is detected by using a threshold value Ref2(B). Thresholdvalue Ref2(B) can simply be provided by the smallest one of thefollowing values. Hereinafter, threshold values Ref2(R), Ref2(G),Ref2(B) are indicated.

(1) Detecting Dust of Achromatic Color High in Lightness

To prevent a cyan line from being detected erroneously as noise, thedifference between a maximum value in lightness (255) and one of thevalues in lightness output from the line sensors other than line sensor213R, i.e., line sensors 213G and 213B, reading a color complementary tored, or cyan, can be set as Ref2(G), Ref2(B). To prevent a magenta linefrom being detected erroneously as noise, the difference between themaximum value in lightness (255) and one of the values in lightnessoutput from the line sensors other than line sensor 213G, i.e., linesensors 213R and 213B, reading a color complementary to green, ormagenta, can be set as Ref2(R), Ref2(B). To prevent a yellow line frombeing detected erroneously as noise, the difference between the maximumvalue in lightness (255) and one of the values in lightness output fromthe line sensors other than line sensor 213B, i.e., line sensors 213Rand 213G, reading a color complementary to blue, or yellow, can be setas Ref2(R), Ref2(G).

(2) Detecting Dust of Achromatic Color Low in Lightness

To prevent a red line from being detected erroneously as noise, thedifference between a minimum value in lightness (0) and one of thevalues in lightness output from the line sensors other than line sensor213R, i.e., line sensors 213G and 213B, reading red color, can be set asRef2(G), Ref2(B). To prevent a green line from being detectederroneously as noise, the difference between the minimum value inlightness (0) and one of the values in lightness output from the linesensors other than line sensor 213G, i.e., line sensors 213R and 213B,reading green color, can be set as Ref2(R), Ref2(B). To prevent a blueline from being detected erroneously as noise, the difference betweenthe minimum value in lightness (0) and one of the values in lightnessoutput from the line sensors other than line sensor 213B, i.e., linesensors 213R and 213G, reading blue color, can be set as Ref2(R),Ref2(G).

Thus more than one threshold value Ref2(R), Ref2(G), Ref2(B) areobtained, and a minimum value thereof can simply be used.

While herein black dust is detected as noise, dust of achromatic colorother than black can also be detected, since any achromatic dust affectsall of R, G and B signals.

Furthermore, while herein a white original is read by way of example, anoriginal of any color other than white may be read.

FIG. 9 is a block diagram showing a configuration of the noise detectionprocessor of the image reading apparatus in the present embodiment. Withreference to the figure, noise detection processor 259 includes firstlightness difference detectors 301R, 301G, 301B extracting from R, G andB signals, respectively, a region having a predetermined feature, secondlightness difference detectors 302R, 302G, 302B extracting from R, G andB signals, respectively, a region having the predetermined feature,detection result extension processors 303R, 303G, 303B extending theregion extracted by the second lightness detectors 302R, 302G, 302B to avicinity thereof, NOR devices 305R, 305G, 305B, AND devices 307R, 307G,307B, a determiner 308, and detected-area extension processors 309R,309G, 309B.

R, G and B signals are input to noise detection processor 259, one lineat a time, sequentially. Note that the R, G and B signals may be inputcollectively by a plurality of lines or an entire image.

The first lightness difference detector 301R receives the R signal andthreshold value Ref1(R) and extracts from the R signal a region havingthe predetermined feature of a first level. This region is a regionhaving a limited variation in lightness and a difference in lightness ofat least threshold Ref1 (R) from a region surrounding it. Such region isonly required to have a size of at least one pixel. In this descriptiona pixel included in a region having the predetermined feature of thefirst level will be referred to as a first feature pixel.

The region having the predetermined feature of the first level may beextracted by employing an edge extraction filter. More than one edgeextraction filter are prepared for sizes of edge regions, respectively,and a value obtained as a result of filtering is compared with thresholdvalue Ref1(R). A pixel satisfying a condition with threshold value Ref1(R) is determined as a center pixel of an edge region and from an edgeextraction filter satisfying that condition the edge region's size isobtained.

FIGS. 10A-10F represent the edge extraction filter by way of example.FIG. 10A represents an edge extraction filter used to detect an edgeregion of a size of one pixel when an R signal is input, one line at atime. FIG. 10B represents an edge extraction filter used to detect anedge region of a size of one pixel when an R signal is input in aplurality of lines correctively.

FIG. 10C represents an edge extraction filter used to detect an edgeregion of a size of three pixels when an R signal is input, one line ata time. FIG. 10D represents an edge extraction filter used to detect anedge region of a size of three pixels when an R signal is input in aplurality of lines correctively.

FIG. 10E represents an edge extraction filter used to detect an edgeregion of a size of five pixels when an R signal is input, one line at atime. FIG. 10D represents an edge extraction filter used to detect anedge region of a size of five pixels when an R signal is input in aplurality of lines correctively.

These edge extraction filters are established under the followingconditions:

(1) An edge region high in lightness is extracted when an average inlightness of pixels A and B minus that in lightness of pixel C equals atleast threshold value Ref1 (R):(Average of Pixels A and B)−(Average of Pixel C)>Ref1(R).

In that case, the center pixel is one of pixels A, B and C that is thehighest in lightness.

(2) An edge region low in lightness is extracted when an average inlightness of pixel C minus that in lightness of pixels A and B equals atleast threshold value Ref1(R):(Average of Pixel C)−(Average of Pixels A and B)>Ref1(R).

In that case, the center pixel is one of pixels A, B and C that is thelowest in lightness.

G and B signals can also be handled with an edge extraction filtersimilar to that used for the R signal.

The first lightness difference detectors 301R, 301G, 301B compare avalue calculated by the above described edge extraction filter withthreshold values Ref1(R), Ref1(G), Ref1(B).

With reference again to FIG. 9, the first feature pixel extracted by thefirst lightness difference detector 301R is represented by a logicalsignal of “1” and a pixel other than the first feature pixel isrepresented by a logical signal of “0” and thus output to AND device307R and determiner 308.

The second lightness difference detector 302R receives the R signal andthreshold value Ref2(R) and extracts from the R signal a region havingthe predetermined feature of a second level. This region is a regionhaving a limited variation in lightness and a difference in lightness ofat least threshold Ref2(R) from a region surrounding it. Such region isonly required to have a size of at least one pixel. In this descriptiona pixel included in a region having the predetermined feature of thesecond level will be referred to as a second feature pixel. It should benoted that threshold value Ref2(R) is a smaller value than thresholdvalue Ref1(R).

The region having the predetermined feature of the second level may beextracted by employing an edge extraction filter. More than one edgeextraction filter are prepared for sizes of edge regions, respectively,and a value obtained as a result of filtering is compared with thresholdvalue Ref2(R). A pixel satisfying a condition with threshold valueRef2(R) is determined as a center pixel of an edge region and from anedge extraction filter satisfying that condition the edge region's sizeis obtained.

The second lightness difference detectors 302R, 302G, 302B compare avalue calculated by the above described edge extraction filter withthreshold values Ref2(R), Ref2(G), Ref2(B).

The second feature pixel extracted by the second lightness differencedetector 302R is represented by a logical signal of “1” and a pixelother than the second feature pixel is represented by a logical signalof “0” and thus output to detection result extension processor 303R.

Detection result extension processor 303R sets a pixel neighboring thesecond feature pixel extracted by the second lightness differencedetector 302R as a second feature pixel to extend a region having thepredetermined feature of the second level. In other words, a pixel thatexists in a vicinity of a pixel of “1” in value as represented by alogical signal received from the second lightness difference detector302R and has a value of “0” is changed to “1”. Noise can be detectedwith higher precision. A logical signal having contributed to extendedregion is output to NOR devices 305G, 305B.

The first lightness difference detector 301G receives the G signal andthreshold value Ref1(G) and extracts from the G signal a region havingthe predetermined feature of the first level. This region is a regionhaving a limited variation in lightness and a difference in lightness ofat least threshold Ref1(G) from a region surrounding it.

The region having the predetermined feature of the first level may beextracted by employing an edge extraction filter. More than one edgeextraction filter are prepared for sizes of edge regions, respectively,and a value obtained as a result of filtering is compared with thresholdvalue Ref1(G). A pixel satisfying a condition with threshold valueRef1(G) is determined as a center pixel of an edge region and from anedge extraction filter satisfying that condition the edge region's sizeis obtained.

The feature pixel extracted by the first lightness difference detector301G is represented by a logical signal of “1” and a pixel other thanthe first feature pixel is represented by a logical signal of “0” andthus output to. AND device 307G and determiner 308.

The second lightness difference detector 302G receives the G signal andthreshold value Ref2(G) and extracts from the G signal a region havingthe predetermined feature of the second level. This region is a regionhaving a limited variation in lightness and a difference in lightness ofat least threshold Ref2(G) from a region surrounding it. Such region isonly required to have a size of at least one pixel. In this descriptiona pixel included in a region having the predetermined feature of thesecond level will be referred to as a second feature pixel. It should benoted that threshold value Ref2(G) is a smaller value than thresholdvalue Ref1(G).

The region having the predetermined feature of the second level may beextracted by employing an edge extraction filter. More than one edgeextraction filter are prepared for sizes of edge regions, respectively,and a value obtained as a result of filtering is compared with thresholdvalue Ref2(G). A pixel satisfying a condition with threshold valueRef2(G) is determined as a center pixel of an edge region and from anedge extraction filter satisfying that condition the edge region's sizeis obtained.

The second feature pixel extracted by the second lightness differencedetector 302G is represented by a logical signal of “1” and a pixelother than the second feature pixel is represented by a logical signalof “0” and thus output to detection result extension processor 303G.

Detection result extension processor 303G sets a pixel neighboring thesecond feature pixel extracted by the second lightness differencedetector 302G as a second feature pixel to extend a region having thepredetermined feature of the second level. A logical signal havingcontributed to an extended region is output to NOR devices 305R, 305B.

The first lightness difference detector 301B receives the B signal andthreshold value Ref1(B) and extracts from the B signal a region havingthe predetermined feature of the first level. This region is a regionhaving a limited variation in lightness and a difference in lightness ofat least threshold Ref1(B) from a region surrounding it.

The region having the predetermined feature of the first level may beextracted by employing an edge extraction filter. More than one edgeextraction filter are prepared for sizes of edge regions, respectively,and a value obtained as a result of filtering is compared with thresholdvalue Ref1(B). A pixel satisfying a condition with threshold valueRef1(B) is determined as a center pixel of an edge region and from anedge extraction filter satisfying that condition-the edge region's sizeis obtained.

The feature pixel extracted by the first lightness difference detector301B is represented by a logical signal of “1” and a pixel other thanthe first feature pixel is represented by a logical signal of “0” andthus output to AND device 307B and determiner 308.

The second lightness difference detector 302B receives the B signal andthreshold value Ref2(B) and extracts from the B signal a region havingthe predetermined feature of the second level. This region is a regionhaving a limited variation in lightness and a difference in lightness ofat least threshold Ref2(B) from a region surrounding it. Such region isonly required to have a size of at least one pixel. In this descriptiona pixel included in a region having the predetermined feature of thesecond level will be referred to as a second feature pixel. It should benoted that threshold value Ref2(B) is a smaller value than thresholdvalue Ref1(B).

The region having the predetermined feature of the second level may beextracted by employing an edge extraction filter. More than one edgeextraction filter are prepared for sizes of edge regions, respectively,and a value obtained as a result of filtering is compared with thresholdvalue Ref2(B). A pixel satisfying a condition with threshold valueRef2(B) is determined as a center pixel of an edge region and from anedge extraction filter satisfying that condition the edge region's sizeis obtained.

The second feature pixel extracted by the second lightness differencedetector 302B is represented by a logical signal of “1” and a pixelother than the second feature pixel is represented by a logical signalof “0” and thus output to detection result extension processor 303B.

Detection result extension processor 303B sets a pixel neighboring thesecond feature pixel extracted by the second lightness differencedetector 302B as a second feature pixel to extend a region having thepredetermined feature of the second level. A logical signal havingcontributed to an extended region is output to NOR devices 305R, 305G.

NOR device 305R receives from each of detection result extensionprocessor 303G, 303B a logical signal having contributed to an extendedregion. NOR device 305R outputs to AND device 307R a logical signalcorresponding to an inversion of an OR of two received logical signals.More specifically, a pixel which is not a second feature pixel foreither a G or B signal is represented by a logical signal of “1” foroutput and a pixel which is a second feature pixel for at least one ofthe signals is represented by a logical signal of “0” for output.

AND device 307R outputs to determiner 308 an AND of a logical signalreceived from the first lightness difference detector 301R and thatreceived from NOR device 305R. More specifically, a pixel which is afirst feature pixel for an R signal and not an extended second featurepixel for either a B or G signal is represented by a logical signal of“1” and a pixel different therefrom is represented by a logical signalof “0” for output. A pixel of “1” in value as represented by thislogical signal indicates a noise pixel. Thus by NOR device 305R and ANDdevice 307R a first feature pixel extracted from an R signal that hasnot been extracted as a second feature pixel for either a G or B signalis determined as a noise pixel.

NOR device 305G receives from each of detection result extensionprocessors 303R, 303B a logical signal having contributed to an extendedregion. NOR device 305G outputs to AND device 307G a logical signalcorresponding to an inversion of an OR of two received logical signals.More specifically, a pixel which is not a second feature pixel foreither an R or B signal is represented by a logical signal of “1” foroutput and a pixel which is a second feature pixel for at least one ofthe signals is represented by a logical signal of “0” for output.

AND device 307G outputs to determiner 308 an AND of a logical signalreceived from the first lightness difference detector 301 G and thatreceived from NOR device 305G. More specifically, a pixel which is afirst feature pixel for a G signal and not an extended second featurepixel for either a R or B signal is represented by a logical signal of“1” and a pixel different therefrom is represented by a logical signalof “0” for output. A pixel of “1” in value as represented by thislogical signal indicates a noise pixel. Thus by NOR device 305G and ANDdevice 307G a first feature pixel extracted from a G signal that has notbeen extracted as a second feature pixel for either an R or B signal isdetermined as a noise pixel.

NOR device 305B receives from each of detection result extensionprocessors 303R, 303G a logical signal having contributed to an extendedregion. NOR device 305B outputs to AND device 307B a logical signalcorresponding to an inversion of an OR of two received logical signals.More specifically, a pixel which is not a second feature pixel foreither an R or G signal is represented by a logical signal of 1” foroutput and a pixel which is a second feature pixel for at least one ofthe signals is represented by a logical signal of “0” for output.

AND device 307B outputs to determiner 308 an AND of a logical signalreceived from the first lightness difference detector 301B and thatreceived from NOR device 305B. More specifically, a pixel which is afirst feature pixel for a B signal and not an extended second featurepixel for either an R or G signal is represented by a logical signal of“1” and a pixel different therefrom is represented by a logical signalof “0” for output. A pixel of “1” in value as represented by thislogical signal indicates a noise pixel. Thus by NOR,device 305B and ANDdevice 307B a first feature pixel extracted from a B signal that has notbeen extracted as a second feature pixel for either an R or G signal isdetermined as a noise pixel.

Determiner 308 receives from the first lightness difference detectors301R, 301G, 301B the logical signal of “1” representing the firstfeature pixel of R, G and B signals each, from AND devices 307R, 307G,307B the logical signal of “1” representing the noise pixel of R, G andB signals each, and from controller 263 the direction in which platen205 is moved. Determiner 308 determines whether or not the pixeldetermined as a noise pixel is valid or not. A detailed description ofdeterminer 308 is given hereinlater.

If detected-area extension processor 309R receives a logical signal of“1” from AND device 307R for a pixel, detected-area extension processor309R sets a pixel that exists in a vicinity of the pixel correspondingto the “1” to a ” 1” to extend a noise pixel's range. This is done toprovide improved precision with which a noise pixel is corrected. Thenoise pixel extended in range is represented by a logical signal of “1”which is in turn output to noise corrector 260.

If detected-area extension processor 309G receives a logical signal of“1” from AND device 307G for a pixel, detected-area extension processor309G sets a pixel that exists in a vicinity of the pixel correspondingto the “1” to a “1” to extend a noise pixel's range. This is done toprovide improved precision with which a noise pixel is corrected. Thenoise pixel extended in range is represented by a logical signal of “1”which is in turn output to noise corrector 260.

If detected-area extension processor 309B receives a logical signal of“1” from AND device 307B for a pixel, detected-area extension processor309B sets a pixel that exists in a vicinity of the pixel correspondingto the “1” to a “1” to extend a noise pixel's range. This is done toprovide improved precision with which a noise pixel is corrected. Thenoise pixel extended in range is represented by a logical signal of “1”which is in turn output to noise corrector 260.

FIG. 11 is a flowchart showing a flow of a determination processfollowed by the determiner of the noise detection processor. Thedetermination is made each time logical signals corresponding to the R,G and B signals are input. Logical signals corresponding to respectiveR, G and B signals are input in the order in which line sensors 213R,213G, 213B output respective R, G and B signals. With reference to FIG.11, in the determination process followed by determiner 308, thedirection in which platen 205 is moved is first provided (step S01).Then, the order in which noise pixels are detected from the R, G and Bsignals is determined (step S02).

Based on the direction in which platen 205 is moved, the order in whichnoise pixels are expected to be detected from the R, G and B signals isdetermined, i.e., it is determined from which signals noise pixels areexpected to be firstly, secondly and thirdly detected respectively. Asignal from which the noise pixel is expected to be detected firstly isherein referred to as first signal, a signal from which the noise pixelis expected to be detected secondly is herein referred to as secondsignal, and a signal from which the noise pixel is expected to bedetected thirdly is herein referred to as third or last signal. Thisorder is determined in the following manner on the basis of the threeconditions.

(1) In the case where platen 205 is moved in the same direction as thatin which the original is transported and at a lower rate than the rateat which the original is transported, the first signal is the R signaloutput from line sensor 213R, the second signal is the G signal outputfrom line sensor 213G and the third signal is the B signal output fromline sensor 213B.

(2) In the case where platen 205 is moved in the same direction as thatin which-the original is transported and at a higher rate than the rateat which the original is transported, the first signal is the B signaloutput from line sensor 213B, the second signal is the G signal outputfrom line sensor 213G and the third signal is the R signal output fromline sensor 213R.

(3) In the case where platen 205 is moved in the opposite direction tothe direction in which the original is transported, the first signal isthe B signal output from line sensor 213B, the second signal is the Gsignal output from line sensor 213G and the third signal is the R signaloutput from line sensor 213R. In this case the relation between themagnitude of the rate at which platen 205 is moved and the magnitude ofthe rate at which the original is transported is irrelevant to the orderin which noise pixels are detected from the signals.

In step S03, logical signals corresponding to the R, G and B signals areinput. Then, noise pixel correction for three logical signals is made(step S04).

FIG. 12 is a flowchart showing a flow of the noise pixel correction instep S04 of FIG. 11. With reference to FIG. 12, in the process of thenoise pixel correction, a target pixel is selected from the first one ofR, G and B signals to determine whether or not the target pixel is anoise pixel (step S21). Here, the target pixel is a pixel to besubjected to the noise pixel correction. Noise detection processor 259receives a logical signal corresponding to the R signal and representinga noise pixel as “1”, a logical signal corresponding to the G signal andrepresenting a noise pixel as “1” and a logical signal corresponding tothe B signal and representing a noise pixel as “1”. Accordingly, in thisnoise pixel correction process, if a target pixel of a logical signalcorresponding to the first signal is “1”, the target pixel is determinedas a noise pixel. Thus, if the target pixel is a noise pixel, theprocess proceeds to step S25. If not, the process proceeds to step S22.

In step S22, it is determined whether or not the target pixel of thefirst signal is a first feature pixel. If so, the process proceeds tostep S23. If not, the process proceeds to step S25. When the processproceeds to step S23, the target pixel of the first signal is not anoise pixel but the first feature pixel. In this case, a target pixel ofthe second signal is a first feature pixel, a target pixel of the thirdsignal is a first feature pixel, or respective target pixels of thesecond and third signals are first feature pixels. In such a case, thetarget pixel of the first signal could be a pixel that reads dustadhering on platen 205. In the following steps, it is determined whetheror not the target pixel of the first signal is a pixel that reads dustadhering on platen 205. Here, in such a case where a target pixel of thefirst signal and a target pixel of the third signal are first featurepixels and a target pixel of the second signal is not a first featurepixel, it is possible for example that white dust adheres on platen 205while a green region of an original is being read.

In step S23, it is determined whether or not the pixel of the precedingline that is at the same position in the main scanning direction as thetarget pixel of the first signal has been determined as a noise pixel.If so, the process proceeds to step S24. If not, the process proceeds tostep S25. This determination is made on the basis of a logical signalthat is previously input to noise detection processor 259 andrepresenting the noise pixel of the line having been subjected to thenoise pixel correction as “1”.

In step S24, the target pixel of the first signal is changed to a noisepixel. Specifically, value “0” of the target pixel of the logical signalcorresponding to the first signal and representing a noise pixel as “1”is changed to “1” Namely, when the target pixel of the first signal isthe first feature pixel and the pixel of the preceding line that is atthe same position in the main scanning direction as the target pixel ofthe first signal is a noise pixel, the target pixel of the first signalis changed to the noise pixel.

The target pixel of the first signal is changed to the noise pixel instep S24 on the condition that:

the target pixel of the first signal is the first feature pixel, atleast one of the target pixel of the second signal and the target pixelof the third signal is the first feature pixel and the pixel of thepreceding line that is at the same position in the main scanningdirection as the target pixel of the first signal is a noise pixel.

In the following step S25, it is determined whether or not the targetpixel of the second signal is a noise pixel. If so, the process proceedsto step S30. If not, the process proceeds to step S26.

In step S26, it is determined whether or not the target pixel of thesecond signal is a first feature pixel. If so, the process proceeds tostep S27. If not, the process proceeds to step S30. When the processproceeds to step S27, the target pixel of the second signal is not anoise pixel but the first feature pixel. In this case, the target pixelof the first signal is a first feature pixel, the target pixel of thethird signal is a first feature pixel, or respective target pixels ofthe first and third signals are first feature pixels. In such a case,the target pixel of the second signal could be a pixel that reads dustadhering on platen 205. In the following steps, it is determined whetheror not the target pixel of the second signal is a pixel that reads dustadhering on platen 205.

In step S27, it is determined whether or not the target pixel of thefirst signal is a noise pixel. If so, the process proceeds to step S29.If not, the process proceeds to step S28. When the target pixel of thefirst signal is a noise pixel, the target pixel of the second signal ischanged to a noise pixel.

In step S28, it is determined whether or not the pixel of the precedingline that is at the same position in the main scanning direction as thetarget pixel of the second signal has been determined as a noise pixel.If so, the process proceeds to step S29. If not, the process proceeds tostep S30. This determination is made on the basis of a logical signalthat is previously input to noise detection processor 259 andrepresenting the noise pixel of the line having been subjected to thenoise pixel correction as “1”.

In step S29, the target pixel of the second signal is changed to a noisepixel. Specifically, value “0” of the target pixel of the logical signalcorresponding to the second signal and representing a noise pixel as “1”is changed to “1”. In step S29, the target pixel of the second signal ischanged to the noise pixel on the following condition:

(1) the target pixel of the second signal is the first feature pixel andthe target pixel of the first signal is the noise pixel, this conditionincluding the condition that respective target pixels of the second andfirst signals are first feature pixels and the pixel of the precedingline that is at the same position in the main scanning direction as thetarget pixel of the first signal is a noise pixel; or

(2) respective target pixels of the second and third signals are firstfeature pixels and the pixel of the preceding line that is at the sameposition in the main scanning direction as the target pixel of thesecond signal is a noise pixel.

In the subsequent step S30, it is determined whether or not the targetpixel of the third signal is a noise pixel. If so, the process proceedsto step S35. If not, the process proceeds to step S31.

In step S31, it is determined whether or not the target pixel of thethird signal is a first feature pixel. If so, the process proceeds tostep S32. If not, the process proceeds to step S35. When the processproceeds to step S32, the target pixel of the third signal is not anoise pixel but the first feature pixel. In this case, the target pixelof the first signal is the first feature pixel, the target pixel of thesecond signal is the first feature pixel, or respective target pixels ofthe first and second signals are the first feature pixels, and it ispossible that the target pixel of the third signal is a pixel that readsdust adhering on platen 205. In the following steps, it is determinedwhether or not the target pixel of the third signal is a pixel thatreads dust adhering on platen 205.

In step S32, it is determined whether or not the target pixel of thesecond signal is a noise pixel. If so, the process proceeds to step S34.If not, the process proceeds to step S33. When the target pixel of thesecond signal is a noise pixel, the target pixel of the third signal isdetermined as a noise pixel.

In step S33, it is determined whether or not the target pixel of thefirst signal is a noise pixel. If so, the process proceeds to step S34.If not, the process proceeds to step S35. Namely, when the target pixelof the first signal is a noise pixel, the target pixel of the thirdsignal is determined as a noise pixel. If the first feature pixel is notdetected from the second signal, the first feature pixel detected fromthe third signal is determined as a noise pixel, in such a case wherewhite dust adheres on platen 205 while a green region of an original isbeing read.

In step S34, the target pixel of the third signal is changed to a noisepixel. Specifically, value “0” of the target pixel of the logical signalcorresponding to the third signal and representing a noise pixel as “1”is changed to “1”. In step S34, the target pixel of the third signal ischanged to the noise pixel on the following condition:

(1) the target pixel of the third signal is the first feature pixel andthe target pixel of the second signal is the noise pixel, this conditionincluding the condition that respective target pixels of the third andsecond signals are first feature pixels and the pixel of the precedingline that is at the same position in the main scanning direction as thetarget pixel of the second signal is a noise pixel; or

(2) the target pixel of the third signal is the first feature pixel andthe target pixel of the first signal is the noise pixel, this conditionincluding the condition that respective target pixels of the third andfirst signals are first feature pixels and the pixel of the precedingline that is at the same position in the main scanning direction as thetarget pixel of the first signal is a noise pixel.

In the subsequent step S35, it is determined whether or not a subsequenttarget pixel is present. If so, the process returns to step S21. If not,the process is ended. In this way, the noise pixel correction is madefor all pixels of logical signals input to noise detection processor259.

With noise pixel corrector 311, first feature pixels extracted from atleast two of the R, G and B signals are corrected to noise pixels on thecondition that, for one of the R, G and B signals, the pixel of thepreceding line that is at the same position in the main scanningdirection as the first feature pixel is a noise pixel. In this way, evenif large dust adheres on platen 205 that results in first feature pixelsextracted from at least two of the R, G and B signals, noise can bedetected from the R, G and B signals.

FIG. 13 is a flowchart showing a flow of a correction process followedby the noise corrector. To noise corrector 260, R, G and B signals andlogical signals corresponding to the R, G and B signals and representinga noise pixel as “1” are input. In the correction process, these signalsare used to correct a noise pixel.

With reference to FIG. 13, a target pixel P of the input R, G and Bsignals for a line is set as a pixel to be processed, and it isdetermined whether or not target pixel P is a noise pixel in any of theR, G and B signals (step S51). If so, the process proceeds to step S52.If not, the process proceeds to step S58.

In step S52, it is determined whether or not target pixel Pr of the Rsignal is a noise pixel. If so, the process proceeds to step S53. Ifnot, the process skips step S53 and proceeds to step S54. In step S53,an R-signal correction is made to correct target pixel Pr of the Rsignal. For example, target pixel Pr may be replaced with the average,maximum or minimum value of a plurality of non-noise pixels neighboringtarget pixel Pr.

In step S54, it is determined whether or not target pixel Pg of the Gsignal is a noise pixel. If so, the process proceeds to step S55. Ifnot, the process skips step S55 and proceeds to step S56. In step S55, aG-signal correction is made to correct target pixel Pg of the G signal.For example, target pixel Pg may be replaced with the average, maximumor minimum value of a plurality of non-noise pixels neighboring targetpixel Pg.

In step S56, it is determined whether or not target pixel Pb of the Bsignal is a noise pixel. If so, the process proceeds to step S57. Ifnot, the process skips step S57 and proceeds to step S58. In step S57, aB-signal correction is made to correct target pixel Pb of the B signal.For example, target pixel Pb may be replaced with the average, maximumor minimum value of a plurality of non-noise pixels neighboring targetpixel Pb.

In step S58, it is determined whether or not there is a pixel to be usedas the next target pixel. If present, the process returns to step S51and repeats the aforementioned procedure. If not, this process is ended.

FIG. 14 is a flowchart showing a flow of the R-signal correction processin step S53 of FIG. 13. With reference to FIG. 14, in the R-signalcorrection process, a search range is set. The search range is definedwith reference to target pixel P.

FIGS. 15A and 15B show exemplary search ranges. In FIGS. 15A and 15B, asignal is represented in two-dimensional form and one box represents onepixel. Pixels within noise 402 are detected as noise pixels. Withreference to FIG. 15A, supposing that a pixel 401 is a target pixel P, asearch range 403 is defined by the range including pixel 401, sevenpixels on the right thereof and seven pixels on the left thereof thatare arranged in the main scanning direction. Here, search range 403 isnot limited to the exemplified size herein shown and may be larger orsmaller than this size. The search range may be any that includes noisepixels and pixels that are not noise pixels.

With reference again to FIG. 14, in step S102, a candidate pixel S isselected from the pixels included in the search range that is set instep S101. In the subsequent step S103, a determination is made as towhether or not the candidate pixel is appropriate for correcting targetpixel P. In the process of making the determination regarding thecandidate pixel, one of a return value indicating the result of thedetermination as to whether or not candidate pixel. S selected in step S102 is appropriate for correcting target pixel P and a return valueindicating that the determination cannot be made is returned.

In the subsequent step S104, the process proceeds to step S105 ifcandidate pixel S selected in step S 102 is appropriate for correctingtarget pixel P. If not, the process proceeds to step S110. If it cannotbe determined whether or not the candidate pixel is appropriate, theprocess proceeds to step S116.

It is determined that a pixel is appropriate as a candidate pixel if allof the following conditions are satisfied:

(1) candidate pixel S is not a noise pixel in any of the R, G and Bsignals; and

(2) for a signal of target pixel P that is not a noise pixel, respectivevalues of target pixel P and candidate pixel S are close to each other.

In step S105, it is determined whether or not target pixel P is a noisepixel that reads white dust. This determination is made by comparingvalue Pr of target pixel P of the R signal with a predetermined value.If value Pr is larger than the predetermined value, it can be determinedthat the target pixel is a noise pixel reading white dust because of thehigh lightness. If it is determined that the target pixel is a noisepixel reading white dust, the process proceeds to step S 106. If not,namely if the target pixel is a noise pixel reading black dust, theprocess proceeds to step S108. Alternatively, a determination may bemade as to whether or not target pixel P is a noise pixel reading blackdust and then it may be determined whether or not value Pr of targetpixel P of the R signal is smaller than a predetermined value. If Pr issmaller than the predetermined value, it can be determined that thetarget pixel is a noise pixel reading black dust because of the lowlightness.

In step S106, it is determined whether or not a value Sr of candidatepixel S of the R signal is smaller than a variable Tmin. If so, theprocess proceeds to step S107. If not, the process skips step S107 andproceeds to step S110. Variable Tmin is a variable for storing theminimum value of value Sr of candidate pixel S of the R signal, amongpixels in the search range, for which the determination ofappropriateness is made in step S103. Here, the initial value ofvariable Tmin is set to a value larger than the maximum value “255” ofthe pixel value.

In step S108, it is determined whether or not value Sr of candidatepixel S of the R signal is larger than a variable Tmax. If so, theprocess proceeds to step S109. If not, the process skips step S109 andproceeds to step S110. Variable Tmax is a variable for storing themaximum value of value Sr of candidate pixel S of the R signal, amongpixels in the search range, for which the determination as toappropriateness is made in step S103. Here, the initial value ofvariable Tmax is set to a value smaller than the minimum value “0” ofthe pixel value.

In step S110, it is determined whether or not the next candidate pixelis present in the search range. If so, the process returns to step S102.If not, the process proceeds to step S111. Namely, all pixels includedin search range 403 are successively set as a candidate pixel (stepS110) and the operation described above is performed on each candidatepixel. Accordingly, as variable Tmin, the minimum value of candidatepixel S of the R signal that is appropriate and included in the searchrange is stored. Variable Tmin is a value for correcting value Pr oftarget pixel P of the R signal when target pixel P of the R signal is anoise pixel resultant from reading white dust. As variable Tmax, themaximum value of the candidate pixel of the R signal that is appropriateand included in the search range is stored. Variable Tmax is a value forcorrecting value Pr of target pixel P of the R signal when target pixelP of the R signal is a noise pixel resultant from reading black dust.

In step S111, it is determined whether or not a value for replacement isdetermined. If target pixel P is a noise pixel reading white dust andvariable Tmin is equal to or smaller than 255, variable Tmin is used asa value for replacement and the process proceeds to step S112. If targetpixel P is a noise pixel reading black dust and variable Tmax is equalto or larger than zero, variable Tmax is used as a value for replacementand the process proceeds to step S112. Otherwise, the process proceedsto step S115.

In step S112, it is determined whether or not target pixel P is a noisepixel reading white dust. If so, the process proceeds to step S113. Ifnot, namely target pixel P is a noise pixel reading black dust, theprocess proceeds to step S114. Alternatively, it may be determinedwhether or not target pixel P is a noise pixel reading black dust.

In step S 113, value Pr of target pixel P of the R signal is set to thevalue stored as variable Tmin that is a value for replacement of thewhite dust. In step S114, value Pr of target pixel P of the R signal isset to the value stored as variable Tmax that is a value for replacementof the black dust. Then this process returns to the correction process.

In step S115, the search range set in step S101 is extended in the subscanning direction and the resultant search range is used as a newsearch range.

FIG. 15B shows an exemplary search range that is generated by extendingthe search range shown in FIG. 15A in the sub scanning direction. InFIG. 15B, a search range 403A has three lines including additional twolines on respective sides of the search range with respect to the subscanning direction, as compared with the search range shown in FIG. 15A.The degree of extension is not limited to the exemplified one and thesearch range may have five lines with additional two lines on each sidewith respect to the sub scanning direction.

With reference again to FIG. 14, in step S115, the extended search rangeis defined and the process returns to step S101. Accordingly, using thenew extended search range, the above-described process is followed.

The process proceeds to step S116 if it cannot be determined whether ornot a pixel in the search range is candidate pixel S appropriate forcorrection. Thus, in step S116, average value Ave of pixels in thesearch range of the R signal is calculated. Naturally, in calculatingaverage value Ave, value Pr of target pixel P of the R signal is notused. In step S117, value Pr of target pixel P of the R signal is set tothe calculated average value Ave and the process is ended.

FIG. 16 is a flowchart showing a flow of the determination process forthe candidate pixel in step S103 of FIG. 14. With reference to FIG. 16,in the process of making the determination regarding the candidatepixel, it is determined whether or not candidate pixel S is a pixelother than a noise pixel in any of the R, G and B signals (step S121).If candidate pixel S is not a noise pixel in any of the R, G and Bsignals, the process proceeds to step S122 and otherwise to step S129.In step S129, the signal “inappropriate” indicating that the candidatepixel is inappropriate for correcting the target pixel is returned tothe R-signal correction process, and the current process is ended.

In step S122, it is determined whether or not target pixel P is a pixelother than a noise pixel in the G signal. If so, the process proceeds tostep S123. If not, the process proceeds to step S127. In step S123, itis determined whether or not target pixel P is a pixel other than anoise pixel in the B signal. If so, the process proceeds to step S124.If not, the process proceeds to step S126.

In step S127, it is determined whether or not target pixel P is a pixelother than a noise pixel in the B signal. If so, the process proceeds tostep S128. If not, the process proceeds to step S131.

The process proceeds to step S124 when the R signal of target pixel P isto be corrected and target pixel P is not a noise pixel in remaining twosignals, i.e., G and B signals. The process proceeds to step S126 or S128 when the R signal of target pixel P is to be corrected and targetpixel P is not a noise pixel in at least one of the remaining G and Bsignals. When the process proceeds to step S126, target pixel P of the Gsignal is not a noise pixel. When the process proceeds to step S128,target pixel P of the B signal is not a noise pixel. When the processproceeds to step S131, target pixel P is a noise pixel in all of the R,G and B signals. In this case, the signal “determination impossible”indicating that the determination as to whether or not the candidatepixel is appropriate cannot be made is returned to the R-signalcorrection process, and the current process is ended.

In step S124, using the fact that target pixel P of the G signal is nota noise pixel, it is determined whether or not the absolute value of thedifference between a value Sg of candidate pixel S of the G signal and avalue Pg of target pixel P of the G signal is equal to or smaller than20. If so, the process proceeds to step S125. If not, the processproceeds to step S129. It is thus determined whether or not value Sg ofcandidate pixel S of the G signal is close to value Pg of target pixel Pof the G signal. The threshold value is not limited to “20”.

In step S125, using the fact that target pixel P of the B signal is nota noise pixel, it is determined whether or not the absolute value of thedifference between a value Sb of candidate pixel S of the B signal and avalue Pb of target pixel P of the B signal is equal to or smaller than20. If so, the process proceeds to step S130. If not, the processproceeds to step S129. It is thus determined whether or not value Sb ofcandidate pixel S of the B signal is close to value Pb of target pixel Pof the B signal. The threshold value is not limited to “20”.

Through steps S124 and S125, candidate pixel S for correcting value Prof target pixel P of the R signal that is a noise pixel is selected.Then, the signal appropriate” indicating that candidate pixel S selectedin step S130 is appropriate for correcting target pixel P is returned tothe R-signal correction process and the current process is ended.

In step S126, using the fact that target pixel P of the G signal is nota noise pixel, it is determined whether or not the absolute value of thedifference between value Sg of candidate pixel S of the G signal andvalue Pg of target pixel P of the G signal is equal to or smaller than20. If so, the process proceeds to step S130. If not, the processproceeds to step S129. It is thus determined whether or not value Sg ofcandidate pixel S of the G signal is close to value Pg of target pixel Pof the G signal. The threshold value is not limited to “20”.

In step S128, using the fact that target pixel P of the B signal is nota noise pixel, it is determined whether or not the absolute value of thedifference between value Sb of candidate pixel S of the B signal andvalue Pb of target pixel P of the B signal is equal to or smaller than20. If so, the process proceeds to step S130. If not, the processproceeds to step S129. It is thus determined whether or not value Sb ofcandidate pixel S of the B signal is close to value Pb of target pixel Pof the B signal. The threshold value is not limited to “20”.

Through step S126 or S128, candidate pixel S for correcting value Pr oftarget pixel P of the R signal that is a noise pixel is selected. Then,the signal “appropriate” indicating that candidate pixel S selected instep S130 is appropriate for correcting target pixel P is returned tothe R-signal correction process and the current process is ended.

FIG. 17 is a flowchart showing a flow of the G-signal correction processin step S55 of FIG. 13. In this flow of the G-signal correction process,any step different from the corresponding one of the R-signal correctionprocess is indicated by a reference with letter “A” added thereto. Inthe following, steps different from those of the R-signal correctionprocess are described.

In step S106A, it is determined whether or not value Sg of candidatepixel S of the G signal is smaller than variable Tmin. If so, theprocess proceeds to step S107A. If not, the process skips step S107A andproceeds to step S110. Variable Tmin is a variable for storing theminimum value of value Sg of candidate pixel S of the G signal, amongpixels in the search range, for which the determination ofappropriateness is made in step S103. Here, the initial value ofvariable Tmin is set to a value larger than the maximum value “255” ofthe pixel value.

In step S108A, it is determined whether or not value Sg of candidatepixel S of the G signal is larger than variable Tmax. If so, the processproceeds to step Si 09A. If not, the process skips step S109A andproceeds to step S110. Variable Tmax is a variable for storing themaximum value of value Sg of candidate pixel S of the G signal, amongpixels in the search range, for which the determination as toappropriateness is made in step S103. Here, the initial value ofvariable Tmax is set to a value smaller than the minimum value “0” ofthe pixel value.

In step S116A, average value Ave of pixels in the search range of the Gsignal is calculated. Naturally, in calculating average value Ave, valuePg of target pixel P of the G signal is not used.

In step S113A, value Pg of target pixel P of the G signal is set to thevalue stored as variable Tmin that is a value for replacement of thewhite dust. In step S114A, value Pg of target pixel P of the G signal isset to the value stored as variable Tmax that is a value for replacementof the black dust. In step S117A, value Pg of target pixel P of the Gsignal is set to average Ave of the G signal in the search range. Thenthis process returns to the correction process.

FIG. 18 is a flowchart showing a flow of the determination process forthe candidate pixel in step S103 of FIG. 17. In this flow, any stepdifferent from the corresponding one of the determination process inFIG. 16 is indicated by a reference with letter “A” added thereto. Inthe following, steps different from those of the determination processin FIG. 16 are chiefly described.

In step S122A, it is determined whether or not target pixel P is a pixelother than a noise pixel in the R signal. If so, the process proceeds tostep S123. If not, the process proceeds to step S127.

The process proceeds to step S124A when the G signal of target pixel Pis to be corrected and target pixel P is not a noise pixel in remainingtwo signals, i.e., R and B signals. The process proceeds to step S126Aor S128 when the G signal of target pixel P is to be corrected andtarget pixel P is not a noise pixel in at least one of the remaining Rand B signals. When the process proceeds to step S126A, target pixel Pof the R signal is not a noise pixel. When the process proceeds to stepS128, target pixel P of the B signal is not a noise pixel. When theprocess proceeds to step S131, target pixel P is a noise pixel in all ofthe R, G and B signals. In this case, the signal “determinationimpossible” indicating that the determination as to whether or not thecandidate pixel is appropriate cannot be made is returned to theR-signal correction process, and the current process is ended.

In step S124A, using the fact that target pixel P of the R signal is nota noise pixel, it is determined whether or not the absolute value of thedifference between value Sr of candidate pixel S of the R signal andvalue Pr of target pixel P of the R signal is equal to or smaller than20. If so, the process proceeds to step S125. If not, the processproceeds to step S129. Thus, it is determined whether or not value Sr ofcandidate pixel S of the R signal is close to value Pr of target pixel Pof the R signal. The threshold value is not limited to “20”.

Through steps S124A and S125, candidate pixel S for correcting value Pgof target pixel P of the G signal that is a noise pixel is selected.Then, the signal “appropriate” indicating that candidate pixel Sselected in step S130 is appropriate for correcting the target pixel isreturned to the G-signal correction process and the current process isended.

In step S126A, using the fact that target pixel P of the R signal is nota noise pixel, it is determined whether or not the absolute value of thedifference between value Sr of candidate pixel S of the R signal andvalue Pr of target pixel P of the R signal is equal to or smaller than20. If so, the process proceeds to step S130. If not, the processproceeds to step S129. Thus, it is determined whether or not value Sr ofcandidate pixel S of the R signal is close to value Pr of target pixel Pof the R signal. The threshold value is not limited to “20”.

Through step S126A or S128, candidate pixel S for correcting value Pg oftarget pixel P of the G signal that is a noise pixel is selected. Then,the signal “appropriate” indicating that candidate pixel S selected instep S130 is appropriate for correcting target pixel P is returned tothe R-signal correction process and the current process is ended.

FIG. 19 is a flowchart showing a flow of the B-signal correction processin step S57 of FIG. 13. In the flow of the B-signal correction process,any step different from the corresponding one of the R-signal correctionprocess is indicated by a reference with letter “B” added thereto. Inthe following, steps of the B-signal correction process different fromthose of the R-signal correction process are described.

In step S106B, it is determined whether or-not value Sb of candidatepixel S of the B signal is smaller than variable Tmin. If so, theprocess proceeds to step S107B. If not, the process skips step S107B andproceeds to step S110. Variable Tmin is a variable for storing theminimum value of value Sb of candidate pixel S of the B signal, amongpixels in the search range, for which the determination ofappropriateness is made in step S103. Here, the initial value ofvariable Tmin is set to a value larger than the maximum value “255” ofthe pixel value.

In step S108B, it is determined whether or not value Sb of candidatepixel S of the B signal is larger than variable Tmax. If so, the processproceeds to step S109B. If not, the process skips step S109B andproceeds to step S110. Variable Tmax is a variable for storing themaximum value of value Sb of candidate pixel S of the B signal, amongpixels in the search range, for which the determination as toappropriateness is made in step S103. Here, the initial value ofvariable Tmak is set to a value smaller than the minimum value “0” ofthe pixel value.

In step S116B, average value Ave of pixels in the search range of the Bsignal is calculated. Naturally, in calculating average value Ave, valuePb of target pixel P of the B signal is not used.

In step S113B, value Pb of target pixel P of the B signal is set to thevalue stored as variable Tmin that is a value for replacement of thewhite dust. In step S114B, value Pb of target pixel P of the B signal isset to the value stored as variable Tmax that is a value for replacementof the black dust. In step S117B, value Pb of target pixel P of the Bsignal is set to calculated average value Ave of the B signal in thesearch range and the process returns to the correction process.

FIG. 20 is a flowchart showing a flow of the determination process forthe candidate pixel in step S103 of FIG. 19. In this flow, any stepdifferent from the corresponding one of the determination process inFIG. 16 is indicated by a reference with letter “B” added thereto. Inthe following, steps different from those of the determination processin FIG. 16 are chiefly described.

In step S123B, it is determined whether or not target pixel P is a pixelother than a noise pixel in the R signal. If so, the process proceeds tostep S124. If not, the process proceeds to step S126.

In step S127B, it is determined whether or not target pixel P is a pixelother than a noise pixel in the R signal. If so, the process proceeds tostep S128B. If not, the process proceeds to step S131.

The process proceeds to step S124 when the B signal of target pixel P isto be corrected and target pixel P is not a noise pixel of remaining twosignals, i.e., R and G signals. The process proceeds to step S126 orS128B when the B signal of target pixel P is to be corrected and targetpixel P is not a noise pixel in at least one of the remaining R and Gsignals. When the process proceeds to step S126, target pixel P of the Gsignal is not a noise pixel. When the process proceeds to step S128B,target pixel P of the R signal is not a noise pixel. When the processproceeds to step S131, target pixel P is a noise pixel in all of the R,G and B signals. In this case, the signal “determination impossible”indicating that the determination as to whether or not the candidatepixel is appropriate cannot be made is returned to the R-signalcorrection process, and the current process is ended.

In step S125B, using the fact that target pixel P of the R signal is nota noise pixel, it is determined whether or not the absolute value of thedifference between value Sr of candidate pixel S of the R signal andvalue Pr of target pixel P of the R signal is equal to or smaller than20. If so, the process proceeds to step S130. If not, the processproceeds to step S129. Thus, it is determined whether or not value Sr ofcandidate pixel S of the R signal is close to value Pr of target pixel Pof the R signal. The threshold value is not limited to “20”.

Through steps S124 and S125B, candidate pixel S for correcting value Pbof target pixel P of the B signal that is a noise pixel is selected.Then, the signal “appropriate” indicating that candidate pixel Sselected in step S130 is appropriate for correcting the target pixel isreturned to the B-signal correction process and the current process isended.

In step S128B, using the fact that target pixel P of the R signal is nota noise pixel, it is determined whether or not the absolute value of thedifference between value Sr of candidate pixel S of the R signal andvalue Pr of target pixel P of the R signal is equal to or smaller than20. If so, the process proceeds to step S130. If not, the processproceeds to step S129. Thus, it is determined whether or not value Sr ofcandidate pixel S of the R signal is close to value Pr of target pixel Pof the R signal. The threshold value is not limited to “20”.

Through step S126 or S128B, candidate pixel S for correcting value Pb oftarget pixel P of the B signal that is a noise pixel is selected. Then,the signal “appropriate” indicating that candidate pixel S selected instep S130 is appropriate for correcting the target pixel is returned tothe R-signal correction process and the current process is ended.

As heretofore discussed, image reading apparatus 10 in the presentembodiment selects a candidate pixel used for correcting a noise pixelfrom pixels of a signal different from the signal with the noise pixel.In other words, the candidate pixel is determined based on pixels ofother data reading the same location of the original as the noise pixel.Thus, noise resultant from reading dust is corrected with a pixelselected from neighboring pixels, and accordingly the image qualityafter the correction can be improved.

Note that while the present embodiment has been described with reader213 fixed to main body 103 by way of example, alternatively, the presentinvention is also applicable to moving reader 213 for scanning. Forexample, the upper restraint plate is of monochromatic color of white orblack, and reader 213 or the source of light 206, reflector mirror 209and reflector member 208 are moved in the sub scanning direction forscanning. During the scan, platen 205 can be oscillated in the subscanning direction to detect dust adhering on platen 205.

Further note that while the search range extends in the main scanningdirection with the target pixel at the center, the search range mayextend in the direction crossing the main scanning direction.Alternatively, a plurality of search ranges extending in differentdirections may be prepared and a search range may be selected therefromthat extends in the direction in which edge pixels in the neighboringregion of the target pixel are arranged.

Although the present invention has been described and illustrated indetail, it is clearly understood that the same is by way of illustrationand example only and is not to be taken by way of limitation, the spiritand scope of the present invention being limited only by the terms ofthe appended claims.

1. An image reading apparatus comprising: a plurality of line sensorsarranged to be mutually spaced in a sub scanning direction to scan anoriginal in the sub scanning direction; a platen arranged between theoriginal and said plurality of line sensors; a mover moving said platenat a rate relative to said plurality of line sensors, said rate beingdifferent from that of the original relative to said plurality of linesensors; an extractor extracting from each of a plurality of data outputfrom said plurality of line sensors a feature pixel having apredetermined feature; a detector comparing pixels of said plurality ofdata corresponding to a single location on the original to detect thefeature pixel extracted from first data of said plurality of data, as anoise pixel if said feature pixel is not a feature pixel for saidplurality of data other than said first data; a second pixel extractorextracting, based on a value of a first pixel present in second datadifferent from said first data and corresponding to the same location onthe original as said noise pixel, a second pixel present in said firstdata for correcting said noise pixel; and a corrector correcting saidnoise pixel based on said extracted second pixel.
 2. The image readingapparatus according to claim 1, further comprising an interlinecorrector synchronizing a plurality of data output by said plurality ofline sensors to be values of pixels reading a single location on theoriginal, wherein said plurality of data synchronized by said interlinecorrector are input, one line at a time, sequentially.
 3. The imagereading apparatus according to claim 1, wherein said second pixelextractor includes a third pixel extractor extracting a third pixelpresent in said second data, having its value within a predeterminedrange relative to the value of said first pixel and located in thevicinity of said first pixel, and said second pixel extractor extracts,as said second pixel, a pixel that is present in said first data,corresponding to the same location on the original as said third pixel,and is not detected as a noise pixel by said detector.
 4. The imagereading apparatus according to claim 3, wherein said second pixelextractor extracts said third pixel from a pixel group selected from aplurality of pixel groups each including a plurality of pixels arrangedin a predetermined direction, and said plurality of pixel groups aredifferent from each other in direction in which said plurality of pixelsare arranged.
 5. The image reading apparatus according to claim 4,wherein said second pixel extractor includes a selector selecting one ofsaid-plurality of pixel groups according to the-direction in which edgepixels around said noise pixel are arranged.
 6. The image readingapparatus according to claim 3, wherein said third pixel extractorextracts said third pixel from a first pixel group including pixelsneighboring said first pixel in a first direction.
 7. The image readingapparatus according to claim 6, wherein said first direction is a mainscanning direction substantially orthogonal to the sub scanningdirection.
 8. The image reading apparatus according to claim 6, whereinsaid third pixel extractor extracts said third pixel from a second pixelgroup larger in the sub scanning direction than said first pixel group,when said third pixel is not extracted from said first pixel group. 9.The image reading apparatus according to claim 1, wherein said correctorreplaces a value of said noise pixel with a value of said second pixel.10. The image reading apparatus according to claim 1, wherein saidcorrector replaces, when said second pixel extractor extracts aplurality of second pixels, a value of said noise pixel with a minimumor maximum value of said plurality of second pixels based on the valueof said noise pixel.
 11. The image reading apparatus according to claim10, wherein said corrector replaces, when said noise pixel is high invalue, the value of said noise pixel with the maximum value of saidplurality of second pixels.
 12. The image reading apparatus according toclaim 10, wherein said corrector replaces, when said noise pixel is lowin value, the value of said noise pixel with the minimum value of saidplurality of second pixels.
 13. The image reading apparatus according toclaim 1, wherein said detector includes an order determination unitdetermining the order in which noise pixels are detected from saidplurality of data, and a noise pixel corrector correcting feature pixelsextracted from at least two data to noise pixels on the condition that apixel of a line preceding a feature pixel of preceding data is a noisepixel.
 14. The image reading apparatus according to claim 13, whereinsaid second pixel extractor identifies a first pixel that is not a noisepixel.
 15. The image reading apparatus according to claim 14, whereinsaid corrector corrects said noise pixel, when said second pixelextractor does not identify said first pixel, using an average ofrespective values of pixels within a predetermined range relative tosaid noise pixel.
 16. The image reading apparatus according to claim 1,wherein said extractor includes an edge extractor extracting an edgeregion and extracts as said feature pixel a pixel included in theextracted edge region.
 17. The image reading apparatus according toclaim 1, wherein said extractor includes a region extractor extracting aregion having a limited variation in lightness and a difference from aneighboring region in lightness of at least a predetermined value, andextracts as said feature pixel a pixel included in said extractedregion.
 18. The image reading apparatus according to claim 1, whereinsaid detector includes an extender setting as said feature pixel a pixelneighboring said feature pixel, and detects said feature pixel extractedfrom one of said plurality of data, as a noise pixel if said featurepixel is not a feature pixel extended by said extender for saidplurality of data other than said one of said plurality of data.
 19. Theimage reading apparatus according to claim 1, wherein said plurality ofline sensors each include a filter different in spectral sensitivity toreceive light reflected from the original through the filter.
 20. Theimage reading apparatus according to claim 1, further comprising anoriginal transporter transporting the original while said plurality ofline sensors scan the original.